Benign and malignant orbital lymphoproliferative disorders: Differentiating using multiparametric MRI at 3.0T

Evaluation of orbital lesions with DCE-MRI: a literature review

PURPOSE

To provide a major review on the applications of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in evaluating orbital lesions. This review also outlines selected scenarios where DCE-MRI may be helpful.

METHODS

A comprehensive retrospective literature review of all English language publications on PubMed, EMBASE, and Google Scholar between 1994 and 2022. This literature review examined the specific applications and clinical scenarios surrounding the utility of DCE-MRI in orbital lesions and various findings that have been presented in the current literature.

RESULTS

DCE-MRI provides information on tissue physiology and permeability, beyond the anatomical features displayed on static imaging. Various measured parameters (qualitative, semi-quantitative, and quantitative) obtained by DCE-MRI have been used to differentiate between benign and malignant lesions, specific orbital lymphoproliferative diseases (OLPD), lacrimal gland lesions, and various rare orbital tumours. DCE-MRI has a limited role as an initial diagnostic imaging modality. However, DCE-MRI may prove to have benefit in predicting and monitoring treatment response in orbital lymphoma as a critical imaging study, but literature specific to orbital malignancies remains limited.

CONCLUSION

The value of DCE-MRI may be in situations of diagnostic uncertainty, where it may be an additional imaging aid following conventional imaging techniques. It may also act as a critical imaging modality for monitoring of orbital tumour treatment response, but the literature remains limited. Standardisation of imaging protocol, measured parameters, and statistical analysis remain limitations of this imaging technique.

Toward Precision Diagnosis: Machine Learning in Identifying Malignant Orbital Tumors With Multiparametric 3 T MRI

BACKGROUND

Orbital tumors present a diagnostic challenge due to their varied locations and histopathological differences. Although recent advancements in imaging have improved diagnosis, classification remains a challenge. The integration of artificial intelligence in radiology and ophthalmology has demonstrated promising outcomes.

PURPOSE

This study aimed to evaluate the performance of machine learning models in accurately distinguishing malignant orbital tumors from benign ones using multiparametric 3 T magnetic resonance imaging (MRI) data.

MATERIALS AND METHODS

In this single-center prospective study, patients with orbital masses underwent presurgery 3 T MRI scans between December 2015 and May 2021. The MRI protocol comprised multiparametric imaging including dynamic contrast-enhanced (DCE), diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), as well as morphological imaging acquisitions. A repeated nested cross-validation strategy using random forest classifiers was used for model training and evaluation, considering 8 combinations of explanatory features. Shapley additive explanations (SHAP) values were used to assess feature contributions, and the model performance was evaluated using multiple metrics.

RESULTS

One hundred thirteen patients were analyzed (57/113 [50.4%] were women; average age was 51.5 ± 17.5 years, range: 19-88 years). Among the 8 combinations of explanatory features assessed, the performance on predicting malignancy when using the most comprehensive model, which is the most exhaustive one incorporating all 46 explanatory features-including morphology, DWI, DCE, and IVIM, achieved an area under the curve of 0.9 [0.73-0.99]. When using the streamlined "10-feature signature" model, performance reached an area under the curve of 0.88 [0.71-0.99]. Random forest feature importance graphs measured by the mean of SHAP values pinpointed the 10 most impactful features, which comprised 3 quantitative IVIM features, 4 quantitative DCE features, 1 quantitative DWI feature, 1 qualitative DWI feature, and age.

CONCLUSIONS

Our findings demonstrate that a machine learning approach, integrating multiparametric MRI data such as DCE, DWI, IVIM, and morphological imaging, offers high-performing models for differentiating malignant from benign orbital tumors. The streamlined 10-feature signature, with a performance close to the comprehensive model, may be more suitable for clinical application.

Diagnostic Performance of Dynamic Contrast-Enhanced 3T MR Imaging for Characterization of Orbital Lesions: Validation in a Large Prospective Study

BACKGROUND AND PURPOSE

Orbital lesions are rare but serious. Their characterization remains challenging. Diagnosis is based on biopsy or surgery, which implies functional risks. It is necessary to develop noninvasive diagnostic tools. The goal of this study was to evaluate the diagnostic performance of dynamic contrast-enhanced MR imaging at 3T when distinguishing malignant from benign orbital tumors on a large prospective cohort.

MATERIALS AND METHODS

This institutional review board-approved prospective single-center study enrolled participants presenting with an orbital lesion undergoing a 3T MR imaging before surgery from December 2015 to May 2021. Morphologic, diffusion-weighted, and dynamic contrast-enhanced MR images were assessed by 2 readers blinded to all data. Univariable and multivariable analyses were performed. To assess diagnostic performance, we used the following metrics: area under the curve, sensitivity, and specificity. Histologic analysis, obtained through biopsy or surgery, served as the criterion standard for determining the benign or malignant status of the tumor.

RESULTS

One hundred thirty-one subjects (66/131 [50%] women and 65/131 [50%] men; mean age, 52 [SD, 17.1] years; range, 19-88 years) were enrolled. Ninety of 131 (69%) had a benign lesion, and 41/131 (31%) had a malignant lesion. Univariable analysis showed a higher median of transfer constant from blood plasma to the interstitial environment (K trans) and of transfer constant from the interstitial environment to the blood plasma (minute-1) (Kep) and a higher interquartile range of K trans in malignant-versus-benign lesions (1.1 minute-1 versus 0.65 minute-1, P = .03; 2.1 minute-1 versus 1.1 minute-1, P = .01; 0.81 minute-1 versus 0.65 minute-1, P = .009, respectively). The best-performing multivariable model in distinguishing malignant-versus-benign lesions included parameters from dynamic contrast-enhanced imaging, ADC, and morphology and reached an area under the curve of 0.81 (95% CI, 0.67-0.96), a sensitivity of 0.82 (95% CI, 0.55-1), and a specificity of 0.81 (95% CI, 0.65-0.96).

CONCLUSIONS

Dynamic contrast-enhanced MR imaging at 3T appears valuable when characterizing orbital lesions and provides complementary information to morphologic imaging and DWI.

Diffusion-Weighted Imaging of the Orbit: A Case Series and Systematic Review

PURPOSE

To describe the findings of diffusion-weighted imaging (DWI) for a series of orbital lesions and provide a systematic review of relevant literature.

METHODS

A retrospective review of 20 patients with orbital lesions who underwent MRI with DWI at two academic institutions between 2015 and 2020 was performed. Lesion diagnosis was histopathologically confirmed except a presumed cavernous hemangioma. Echoplanar diffusion-weighted images had been acquired using 2 or 3 b values (b=0 and 1000 or b=0, 500, and 1000) at 1.5T or 3T. Lesions with significant artifacts were excluded. DWI sequences were analyzed by neuro-radiologists blinded to the diagnosis. Mean ADC values of lesions were calculated from a single region of interest. An independent two-tailed t test was used to compare categories of lesions with p < 0.05 considered significant. A systematic review of the literature was performed.

RESULTS

Our study included 21 lesions. ADC values were significantly lower for malignant lesions (0.628 ± 0.125 × 10 -3 mm 2 /s) than inflammatory lesions (1.167 ± 0.381 × 10 -3 mm 2 /s) ( p < 0.001). ADC values were significantly lower for orbital lymphoma (mean 0.621 ± 0.147 × 10 -3 mm 2 /s) than idiopathic orbital inflammation (mean 1.188 ± 0.269 × 10 -3 mm 2 /s) with no overlap ( p < 0.001).

CONCLUSIONS

Orbital malignancies demonstrated lower ADC values, while inflammatory processes demonstrated higher ADC values, except IgG4-related disease. DWI and ADC values differentiated idiopathic orbital inflammation from orbital lymphoma. This study highlights the role of DWI in evaluating orbital pathology.

Diagnostic Utility of Diffusion-Weighted Imaging and Apparent Diffusion Coefficient for Common Orbital Lesions: A Review

PURPOSE

To review and summarize the existing literature surrounding the clinical use of diffusion-weighted imaging and apparent diffusion coefficient (ADC) as diagnostic tools in differentiating common orbital lesions.

METHODS

A systematic literature review on the use of ADC and diffusion-weighted imaging sequences for orbital imaging was performed. Only original research articles that reported ADC values for benign or malignant lesions were included.

RESULTS

Malignant orbital tumors have an overall lower mean ADC value than benign masses. Orbital lymphoma is characterized by consistently lower ADC values compared with other malignant orbital masses; a threshold value less than 0.775 × 10 -3 mm 2 /s has been proposed to distinguish orbital lymphoma from other neoplastic and non-neoplastic orbital masses. To differentiate orbital inflammatory disease from lymphoma, an ADC threshold greater than 0.92 × 10 -3 mm 2 /s has been proposed.

CONCLUSIONS

Orbital masses encompass a host of benign and malignant etiologies and can present a diagnostic challenge on both clinical and radiological assessment. Recent advanced MRI techniques such as diffusion-weighted imaging and ADC can improve the diagnostic specificity for orbital disease, particularly in differentiating benign from malignant lesions and lymphoma from orbital inflammatory disease.

Radiological Determinants of Complicated Immunoglobulin G4-Related Ophthalmic Disease: A Territory-Wide Cohort Study

PURPOSE

To evaluate the presenting radiological features of immunoglobulin G4-related ophthalmic disease (IgG4-ROD) and their associations with IgG4-related optic neuropathy (IgG4-RON), and IgG4-related ocular adnexal lymphoma (IgG4-ROL).

METHODS

A territory-wide, biopsy-proven, Chinese cohort. Masked review of orbital images, medical records, and histopathology reports.

RESULTS

A total of 115 (94%) of the 122 patients in our cohort had preoperative orbital images (computed tomography=105, magnetic resonance imaging=40). Among them, 103/115 (90%) showed enlarged lacrimal glands, and 91 (88%) were bilateral. Nerve enlargement was observed: infraorbital in 31/115 (27%) patients and frontal in 17/115 (15%), 10 and 9 being bilateral, respectively. At least 1 or more extraocular muscle (EOM) enlargement was found in 41/115 (37%) patients, bilaterally in 20. Lateral rectus occurred in 30 (73%) of these 41 EOM patients and inferior rectus in 28 (68%). Two adjacent EOMs (inferior and lateral recti in 11 patients, inferior and medial recti in 7 patients) or multiple EOMs (at least 3) were enlarged in 23/41 (56%) and 13/41 (32%) of the patients, respectively. Intraconal lesions (67% vs 11%, P<0.05), infraorbital (83% vs 23%, P<0.005), or frontal (50% vs 15%, P<0.05) nerve enlargement was significantly associated with IgG4-RON (6 patients) by univariate analyses. Asymmetric lacrimal gland enlargement and discrete orbital mass (both P<0.05) were associated with IgG4-ROL (9 patients) by multivariate analyses.

CONCLUSIONS

In this IgG4-ROD cohort, most patients had bilateral enlarged lacrimal glands, and the lateral rectus is the most frequently involved EOM. For the first time, unique radiological patterns associated with the development of IgG4-RON and IgG4-ROL are found.

MRI‐Based Radiomics Nomogram for Preoperative Differentiation Between Ocular Adnexal Lymphoma and Idiopathic Orbital Inflammation

BACKGROUND

Ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI) are malignant and benign lesions for which radiotherapy and corticosteroids are indicated, but similar clinical manifestations make their differentiation difficult.

PURPOSE

To develop and validate an MRI-based radiomics nomogram for individual diagnosis of OAL vs. IOI.

STUDY TYPE

Retrospective.

POPULATION

A total of 103 patients (46.6% female) with mean age of 56.4 ± 16.3 years having OAL (n = 58) or IOI (n = 45) were divided into an independent training (n = 82) and a testing dataset (n = 21).

FIELD STRENGTH/SEQUENCE

A 3-T, precontrast T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and postcontrast T1WI (T1 + C).

ASSESSMENT

Radiomics features were extracted and selected from segmented tumors and peritumoral regions in MRI before-and-after filtering. These features, alone or combined with clinical characteristics, were used to construct a radiomics or joint signature to differentiate OAL from IOI, respectively. A joint nomogram was built to show the impact of the radiomics signature and clinical characteristics on individual risk of developing OAL.

STATISTICAL TESTS

Area under the curve (AUC) and accuracy (ACC) were used for performance evaluation. Mann-Whitney U and Chi-square tests were used to analyze continuous and categorical variables. Decision curve analysis, kappa statistics, DeLong and Hosmer-Lemeshow tests were also conducted. P < 0.05 was considered statistically significant.

RESULTS

The joint signature achieved an AUC of 0.833 (95% confidence interval [CI]: 0.806-0.870), slightly better than the radiomics signature with an AUC of 0.806 (95% CI: 0.767-0.838) (P = 0.778). The joint and radiomics signatures were comparable to experienced radiologists referencing to clinical characteristics (ACC = 0.810 vs. 0.796-0.806, P > 0.05) or not (AUC = 0.806 vs. 0.753-0.791, P > 0.05), respectively. The joint nomogram gained more net benefits than the radiomics nomogram, despite both showing good calibration and discriminatory efficiency (P > 0.05).

DATA CONCLUSION

The developed radiomics-based analysis might help to improve the diagnostic performance and reveal the association between radiomics features and individual risk of developing OAL.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: 3.

A deep learning model combining multimodal radiomics, clinical and imaging features for differentiating ocular adnexal lymphoma from idiopathic orbital inflammation

OBJECTIVES

To evaluate the value of deep learning (DL) combining multimodal radiomics and clinical and imaging features for differentiating ocular adnexal lymphoma (OAL) from idiopathic orbital inflammation (IOI).

METHODS

Eighty-nine patients with histopathologically confirmed OAL (n = 39) and IOI (n = 50) were divided into training and validation groups. Convolutional neural networks and multimodal fusion layers were used to extract multimodal radiomics features from the T1-weighted image (T1WI), T2-weighted image, and contrast-enhanced T1WI. These multimodal radiomics features were then combined with clinical and imaging features and used together to differentiate between OAL and IOI. The area under the curve (AUC) was used to evaluate DL models with different features under five-fold cross-validation. The Student t-test, chi-squared, or Fisher exact test was used for comparison of different groups.

RESULTS

In the validation group, the diagnostic AUC of the DL model using combined features was 0.953 (95% CI, 0.895-1.000), higher than that of the DL model using multimodal radiomics features (0.843, 95% CI, 0.786-0.898, p < 0.01) or clinical and imaging features only (0.882, 95% CI, 0.782-0.982, p = 0.13). The DL model built on multimodal radiomics features outperformed those built on most bimodalities and unimodalities (p < 0.05). In addition, the DL-based analysis with the orbital cone area (covering both the orbital mass and surrounding tissues) was superior to that with the region of interest (ROI) covering only the mass area, although the difference was not significant (p = 0.33).

CONCLUSIONS

DL-based analysis that combines multimodal radiomics features with clinical and imaging features may help to differentiate between OAL and IOI.

KEY POINTS

• It is difficult to differentiate OAL from IOI due to the overlap in clinical and imaging manifestations. • Radiomics has shown potential for noninvasive diagnosis of different orbital lymphoproliferative disorders. • DL-based analysis combining radiomics and imaging and clinical features may help the differentiation between OAL and IOI.

Correlation Between IVIM-DWI Parameters and Pathological Classification of Idiopathic Orbital Inflammatory Pseudotumors: A Preliminary Study

Objective

To investigate the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and the pathological classification of idiopathic orbital inflammatory pseudotumors (IOIPs).

Methods

Nineteen patients who were diagnosed with IOIPs (a total of 24 affected eyes) between November 2018 and December 2020 were included in the study. All the patients underwent magnetic resonance imaging orbital plain scans and IVIM-DWI multiparameter scans before an operation. The true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) values were obtained. Based on histopathology, the lesions were divided into three types: lymphocytic infiltration, fibrosclerotic, and mixed. The correlation between IVIM-DWI parameters and pathological classification was tested with the histopathological results as the gold standard. The data were analyzed using SPSS version 17.0, with P < 0.05 defined as significant.

Results

Among the 19 patients (24 eyes) affected by IOIP, there were no significant differences between IOIP pathological classification and gender or age (P > 0.05). There were statistically significant differences between the D and f values for different pathological types of IOIP and IVIM parameters (P < 0.05), and there was no significant difference in D* value between the different pathological types (P > 0.05).

Conclusion

The D and f values showed correlation with different types of IOIP, and the sensitivity of the D value was higher than that of the f value. The D* value showed no significant distinction between pathological types of IOIP.

Histogram analysis of dynamic contrast-enhanced magnetic resonance imaging in the differential diagnosis of parotid tumors

Objective

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) histograms were used to investigate whether their parameters can distinguish between benign and malignant parotid gland tumors and further differentiate tumor subgroups.

Materials and methods

A total of 117 patients (32 malignant and 85 benign) who had undergone DCE-MRI for pretreatment evaluation were retrospectively included. Histogram parameters including mean, median, entropy, skewness, kurtosis and 10th, 90th percentiles were calculated from time to peak (TTP) (s), wash in rate (WIR) (l/s), wash out rate (WOR) (l/s), and maximum relative enhancement (MRE) (%) mono-exponential models. The Mann–Whitney U test was used to compare the differences between the benign and malignant groups. The diagnostic value of each significant parameter was determined on Receiver operating characteristic (ROC) analysis. Multivariate stepwise logistic regression analysis was used to identify the independent predictors of the different tumor groups.

Results

For both the benign and malignant groups and the comparisons among the subgroups, the parameters of TTP and MRE showed better performance among the various parameters. WOR can be used as an indicator to distinguish Warthin’s tumors from other tumors. Warthin’s tumors showed significantly lower values on 10th MRE and significantly higher values on skewness TTP and 10th WOR, and the combination of 10th MRE, skewness TTP and 10th WOR showed optimal diagnostic performance (AUC, 0.971) and provided 93.12% sensitivity and 96.70% specificity. After Warthin’s tumors were removed from among the benign tumors, malignant parotid tumors showed significantly lower values on the 10th TTP (AUC, 0.847; sensitivity 90.62%; specificity 69.09%; P < 0.05) and higher values on skewness MRE (AUC, 0.777; sensitivity 71.87%; specificity 76.36%; P < 0.05).

Conclusion

DCE-MRI histogram parameters, especially TTP and MRE parameters, show promise as effective indicators for identifying and classifying parotid tumors. Entropy TTP and kurtosis MRE were found to be independent differentiating variables for malignant parotid gland tumors. The 10th WOR can be used as an indicator to distinguish Warthin’s tumors from other tumors.

Discriminating between IgG4-related orbital disease and other causes of orbital inflammation with intra voxel incoherent motion (IVIM) MR imaging at 3T

PURPOSE

The purpose of this prospective study was to determine the capabilities of intravoxel incoherent motion (IVIM) MRI at 3 Tesla in discriminating between IgG4-related orbital disease (IgG4-ROD) and other causes of orbital inflammation.

MATERIALS AND METHODS

Main selection criteria for the patients enrolled in this prospective study were age over 18 years and histopathologicaly proven orbital inflammatory lesion. MRI examinations were performed prior to surgery and treatment in all patients with suspected orbital inflammation. Two neuroradiologists, blinded to clinical data, independently analyzed structural MRI examinations and IVIM sequences obtained with 15 b values ranging from 0 to 2000 s/mm². Apparent diffusion coefficient (ADC), "true" diffusion coefficient (D), perfusion fraction (f) and pseudodiffusion coefficient (D*) values were calculated from all orbital lesions. Diagnostic capabilities of IVIM parameters were assessed using receiver operating-characteristic (ROC) curves and area under the curve (AUC). Sensitivity, specificity, and accuracy of IVIM parameters were calculated for the best threshold values and reported with their corresponding 95% confidence intervals (CI).

RESULTS

Thirty-five patients (21 women and 14 men; mean age, 49.2 ± 13.75 [SD] years; age range: 23-77 years) with 48 orbital lesions were enrolled in the study. Fifteen patients (15/35; 43%) had IgG4-ROD and 20 (20/35; 57%) had other causes of orbital inflammation. Median D value was significantly greater in patients with IgG4-ROD (1 × 10^-3 mm²/s; interquartile range [IQR]: 0.9 × 10^-3; 1.2 × 10^-3) as compared to patients with non IgG4-ROD (0.80 × 10^-3 mm²/s; IQR: 0.7 × 10^-3; 1 × 10^-3) (P = 0.04). There was no significant difference for ADC, f or D*. Area under the curve were of 0.54, 0.73, 0.63 and 0.56 for ADC, D, f and D*, respectively. Optimal threshold derived from ROC curves for D was 0.87 × 10^-3 mm²/s, yielding 92% sensitivity (95% CI: 62-100%) and 71% specificity (95% CI: 44-90%) for the diagnosis of IgG4-ROD. No differences in standard morphological MRI criteria were found between IgG4-ROD and non IgG4-ROD.

CONCLUSION

Our study shows that IVIM MRI is a useful imaging technique to distinguish IgG4-ROD from other causes of orbital inflammation.

Longitudinal Multiparametric MRI Assessment of Irradiated Salivary Gland in a Rat Model: Correlated With Histological Findings

BACKGROUND

Several magnetic resonance imaging (MRI) sequences have been applied to assess injured glands but without histological validation.

PURPOSE

To evaluate longitudinal changes in multiparametric MRI (mp-MRI) of irradiated salivary glands in a rat model and investigate correlations between mp-MRI and histological findings.

STUDY TYPE

Prospective.

ANIMAL MODEL

Submandibular glands of 36 rats were radiated using a single dose of 15 Gy X-ray (irradiation [IR] group), and 6 other rats were enrolled into sham-IR group. mp-MRI were scanned 1 day after sham-IR (n = 6), or 1, 2, 4, 8, 12, 24 weeks after IR (n = 36, 6 per subgroup).

FIELD STRENGTH/SEQUENCE

A 3.0-T/Diffusion-weighted imaging (DWI), readout-segmented echo-planar imaging (EPI) sequence; intravoxel incoherent motion DWI, single-shot EPI sequence; T1 mapping, dual-flip-angle gradient-echo sequence with volumetric interpolated breath-hold examination; T2 mapping, turbo spin-echo sequence.

ASSESSMENT

Parameters including apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D^* ), perfusion fraction (f), T1 and T2 value were obtained. Histological examinations, including hematoxylin and eosin staining (for acinar cell fraction [AC%] detection), Masson's trichrome staining (for degree of fibrosis [F%] determination) and CD34-immunohistochemical staining (for microvessel density [MVD] calculation), were performed at corresponding time points.

STATISTICAL TESTS

One-way analysis of variance was used to compare the mp-MRI and histological parameters among different groups. Spearman correlation analysis was applied to determine the correlation between mp-MRI and histological parameters. Two-sided P ≤ 0.05 was considered statistically significant.

RESULTS

Changes of mp-MRI parameters (ADC, D, D^* , f, T1, T2) and histological results (AC%, F%, MVD) among the seven groups were all significant. ADC, D, and T2 values negatively correlated with AC% (ADC, r = -0.728; D, r = -0.773; T2, r = -0.600), f positively correlated with MVD (r = 0.496), and T1 values positively correlated with F% (r = 0.714). DATA CONCLUSION: mp-MRI might be able to noninvasively and quantitatively evaluate the dynamic pathological changes within the irradiated salivary glands.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Texture analysis of dual-phase contrast-enhanced CT in the diagnosis of cervical lymph node metastasis in patients with papillary thyroid cancer

BACKGROUND

Computed tomography texture analysis (CTTA) provides objective and quantitative information regarding tumor heterogeneity beyond visual inspection. However, no study has yet used CTTA to differentiate metastatic from non-metastatic cervical lymph node in patients with papillary thyroid cancer (PTC).

PURPOSE

To evaluate the value of texture analysis of dual-phase contrast-enhanced CT images in diagnosing cervical lymph node metastasis in patients with PTC.

MATERIAL AND METHODS

Metastatic (n = 27) and non-metastatic (n = 32) cervical lymph nodes were analyzed retrospectively. Texture analyses were performed on both arterial (A) and venous (V) phase CT images. Texture parameters, including mean gray-level intensity, skewness, kurtosis, entropy, and uniformity, were obtained and compared between groups. Receiver operating characteristic (ROC) curves analyses and multivariate logistic regression analysis were used in our study.

RESULTS

Metastatic lymph nodes showed significantly higher A-mean gray-level intensity, A-entropy, and lower A-kurtosis and V-kurtosis (all P < 0.001) than non-metastatic mimics. The ROC curve analyses indicated that A-kurtosis demonstrated an optimal diagnostic area under the curve (AUC; 0.884) and specificity (92.59%), while the A-mean gray-level intensity showed optimal diagnostic sensitivity (90.62%). Multivariate logistic regression analysis showed that A-mean gray-level intensity (P = 0.006, odds ratio [OR] = 24.297) and V-kurtosis (P = 0.014, OR = 19.651) were the independent predictor for metastatic cervical lymph node.

CONCLUSION

Dual-phase contrast-enhanced CCTA-especially A-mean gray-level intensity and V-kurtosis-may have the potential to diagnose metastatic cervical lymph node in patients with PTC.

Advances in magnetic resonance imaging of orbital disease

Magnetic resonance imaging (MRI) is increasingly used by the orbital surgeon to aid in the diagnosis, surgical planning, and monitoring of orbital disease. MRI provides superior soft tissue detail compared with computed tomography or ultrasound, and advancing techniques enhance its ability to highlight abnormal orbital pathology. Diffusion-weighted imaging is a specialized technique that uses water molecule diffusion patterns in tissue to generate contrast signals and can help distinguish malignant from benign lesions. Steady-state free precession sequences such as Constructive Interference in Steady-State (CISS) and Fast Imaging Employing Steady-state Acquisition (FIESTA) generate highly detailed, 3-dimensional reconstructed images and are particularly useful in distinguishing structures adjacent to cerebral spinal fluid. Magnetic resonance angiography can be used to characterize vascular lesions within the orbit. New developments in magnetic field strength as well as the use of orbital surface coils achieve increasingly improved imaging resolution.

To Explore MR Imaging Radiomics for the Differentiation of Orbital Lymphoma and IgG4-Related Ophthalmic Disease

Among orbital lymphoproliferative disorders, about 55% of diagnosed cancerous tumors are orbital lymphomas, and nearly 50% of benign cases are immunoglobulin G4-related ophthalmic disease (IgG4-ROD). However, due to nonspecific characteristics, the differentiation of the two diseases is challenging. In this study, conventional magnetic resonance imaging-based radiomics approaches were explored for clinical recognition of orbital lymphomas and IgG4-ROD. We investigated the value of radiomics features of axial T1- (T1WI-) and T2-weighted (T2WI), contrast-enhanced T1WI in axial (CE-T1WI) and coronal (CE-T1WI-cor) planes, and 78 patients (orbital lymphoma, 36; IgG4-ROD, 42) were retrospectively reviewed. The mass lesions were manually annotated and represented with 99 features. The performance of elastic net-based radiomics models using single or multiple modalities with or without feature selection was compared. The demographic features showed orbital lymphoma patients were significantly older than IgG4-ROD patients (p < 0.01), and most of the patients were male (72% in the orbital lymphoma group vs. 23% in the IgG4-ROD group; p = 0.03). The MR imaging findings revealed orbital lymphomas were mostly unilateral (81%, p = 0.02) and wrapped eyeballs or optic nerves frequently (78%, p = 0.02). In addition, orbital lymphomas showed isointense in T1WI (100%, p < 0.01), and IgG4-ROD was isointense (60%, p < 0.01) or hyperintense (40%, p < 0.01) in T1WI with well-defined shape (64%, p < 0.01). The experimental comparison indicated that using CE-T1WI radiomics features achieved superior results, and the features in combination with CE-T1WI-cor features and the feature preselection method could further improve the classification performance. In conclusion, this study comparatively analyzed orbital lymphoma and IgG4-ROD from demographic features, MR imaging findings, and radiomics features. It might deepen our understanding and benefit disease management.

Arterial spin labeling and diffusion-weighted MR imaging: Utility in differentiating idiopathic orbital inflammatory pseudotumor from orbital lymphoma

PURPOSE

To assess arterial spin-labeling (ASL) and diffusion-weighted imaging (DWI) and in combination for differentiating between idiopathic orbital inflammatory pseudotumor (IOIP) and orbital lymphoma.

MATERIAL AND METHODS

A retrospective study was done on 37 untreated patients with orbital masses, suspected to be IOIP or orbital lymphoma that underwent ASL and DWI of the orbit. Quantitative measurement of tumor blood flow (TBF) and apparent diffusion coefficient (ADC) of the orbital lesion was done.

RESULTS

There was a significant difference (P = 0.001) in TBF between patients with IOIP (n = 21) (38.1 ± 6.2, 40.3 ± 7.1 ml/100 g/min) and orbital lymphoma (n = 16) (55.5 ± 7.1, 56.8 ± 7.9 ml/100 g/min) for both observers respectively. Thresholds of TBF used for differentiating IOIP from orbital lymphoma were 48, 46 ml/100 g/min revealed area under the curve (AUC) of (0.958 and 0.921), and accuracy of (86% and 83%) for both observers respectively. There was a significant difference (P = 0.001) in ADC between patients with IOIP (1.04 ± 0.19, 1.12 ± 0.23 × 10^-3 mm²/s) and orbital lymphoma (0.69 ± 0.10, 0.72 ± 0.11 × 10^-3 mm²/s) for both observers respectively. Thresholds of ADC used for differentiating IOIP from orbital lymphoma were 0.84 and 0.86 × 10^-3 mm²/s with AUC of (0.933 and 0.920), and accuracy of 89% and 90% for both observers respectively. The combined TBF and ADC used for differentiating IOIP from orbital lymphoma had AUC of (0.973 and 0.970) and accuracy of (91% and 89%) for both observers respectively.

CONCLUSION

TBF and ADC alone and in combination are useful for differentiating IOIP from orbital lymphoma.

Improving diagnostic performance of differentiating ocular adnexal lymphoma and idiopathic orbital inflammation using intravoxel incoherent motion diffusion-weighted MRI

PURPOSE

To investigate the utility of intravoxel incoherent motion diffusion-weighted MRI (IVIM-DWI) derived diffusion and perfusion parameters in differentiating ocular adnexal lymphoma (OAL) from idiopathic orbital inflammation (IOI), and to assess whether IVIM-DWI provides improved diagnostic performance for the distinction.

METHOD

Twenty-one patients with OAL and 24 patients with IOI underwent IVIM-DWI. Apparent diffusion coefficient (ADC) and IVIM-DWI parameters including true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were measured in lesions by two independent radiologists. The MRI parameter differences between OAL and IOI were tested using two-sample t-test. The receiver operating characteristic (ROC) analysis curves were used to determine the diagnostic performance of significant parameters for differentiation between OAL and IOI.

RESULTS

The ADC, D, and f were lower in OAL than those in IOI (ADC = 0.78 ± 0.12 vs. 0.99 ± 0.16 × 10^-3 mm²/s, P < 0.001; D = 0.34 ± 0.15 vs. 0.76 ± 0.25 × 10^-3 mm²/s, P < 0.001; f = 0.31 ± 0.06 vs. 0.41 ± 0.08 × 100 %, P < 0.001). There was no significant difference in D* between OAL and IOI (P = 0.235). The optimal cut-off values of ADC, D, and f in differentiating OAL from IOI were 0.83 × 10^-3 mm²/s, 0.56 × 10^-3 mm²/s, and 0.36 × 100 %, respectively. No significant differences were found in areas under the curve (AUCs) among ADC, D and f (all P > 0.05). The combination of D and f provided significantly higher AUC than ADC (AUC = 0.984 vs. 0.838, Z = 2.128, P = 0.033), and had higher sensitivity of 95.24 %, specificity of 95.83 %, and accuracy of 95.56 %.

CONCLUSIONS

IVIM-DWI is valuable in differentiating OAL from IOI, and D combined f can improve the performance of differential diagnosis.

Bag-of-features-based radiomics for differentiation of ocular adnexal lymphoma and idiopathic orbital inflammation from contrast-enhanced MRI

OBJECTIVES

To evaluate the effectiveness of bag-of-features (BOF)-based radiomics for differentiating ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI) from contrast-enhanced MRI (CE-MRI).

METHODS

Fifty-six patients with pathologically confirmed IOI (28 patients) and OAL (28 patients) were randomly divided into training (n = 42) and testing (n = 14) groups. One hundred sixty texture features extracted from the CE-MR image were encoded into the BOF representation with fewer features. The support vector machine (SVM) with a linear kernel was used as the classifier. Data augmented was performed by cropping orbital lesions in different directions to alleviate the over-fitting problem. Student's t test and the Holm-Bonferroni method were employed to compare the performance of different analysis methods. The chi-square test was used to compare the analysis with MRI and human radiological diagnosis.

RESULTS

In the independent testing group, the differentiation by the BOF features with augmentation achieved an area under the curve (AUC) of 0.803 (95% CI: 0.725-0.880), which was significantly higher than that of the BOF features without augmentation and that of the texture features (p < 0.05). In addition, the same radiomic analysis with pre-contrast MRI obtained an AUC of 0.618 (95% CI: 0.560-0.677), which was significantly lower than that with CE-MRI. The diagnostic performance of the analysis with CE-MRI was significantly better than the radiology resident (p < 0.05) but had no significant difference with the experienced radiologist, even though there was less consistency between the radiomic analysis and the human visual diagnosis.

CONCLUSIONS

The BOF-based radiomics may be helpful for the differentiation between OAL and IOI.

KEY POINTS

• It is challenging to differentiate OAL from IOI due to the similar clinical and image features. • Radiomics has great potential for the noninvasive diagnosis of orbital diseases. • The BOF representation from patch to image may help the differentiation of OAL and IOI.

Intravoxel incoherent motion (IVIM) 3 T MRI for orbital lesion characterization

OBJECTIVES

To determine the diagnostic accuracy of MRI intravoxel incoherent motion (IVIM) when characterizing orbital lesions, which is challenging due to a wide range of locations and histologic types.

METHODS

This IRB-approved prospective single-center study enrolled participants presenting with an orbital lesion undergoing a 3-T MRI prior to surgery from December 2015 to July 2019. An IVIM sequence with 15 b values ranging from 0 to 2000 s/mm² was performed. Two neuroradiologists, blinded to clinical data, individually analyzed morphological MRIs. They drew one region of interest inside each orbital lesion, providing apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion fraction (f), and pseudodiffusion coefficient (D*) values. T test, Mann-Whitney U test, and receiver operating characteristic curve analyses were performed to discriminate between orbital lesions and to determine the diagnostic accuracy of the IVIM parameters.

RESULTS

One hundred fifty-six participants (84 women and 72 men, mean age 54.4 ± 17.5 years) with 167 orbital lesions (98/167 [59%] benign lesions including 54 orbital inflammations and 69/167 [41%] malignant lesions including 32 lymphomas) were included in the study. ADC and D were significantly lower in malignant than in benign lesions: 0.8 × 10^-3 mm²/s [0.45] versus 1.04 × 10^-3 mm²/s [0.33], p < 0.001, and 0.75 × 10^-3 mm²/s [0.40] versus 0.98 × 10^-3 mm²/s [0.42], p < 0.001, respectively. D* was significantly higher in malignant lesions than in benign ones: 12.8 × 10^-3 mm²/s [20.17] versus 7.52 × 10^-3 mm²/s [7.57], p = 0.005. Area under curve was of 0.73, 0.74, 0.72, and 0.81 for ADC, D, D*, and a combination of D, f, and D*, respectively.

CONCLUSIONS

Our study showed that IVIM might help better characterize orbital lesions.

KEY POINTS

• Intravoxel incoherent motion (IVIM) helps clinicians to assess patients with orbital lesions. • Intravoxel incoherent motion (IVIM) helps clinicians to characterize orbital lymphoma versus orbital inflammation. • Management of patients becomes more appropriate.

Added value of susceptibility-weighted imaging to diffusion-weighted imaging in the characterization of parotid gland tumors

PURPOSE

To assess the added value of susceptibility-weighted imaging (SWI) to diffusion-weighted imaging (DWI) in the characterization of parotid gland tumors.

METHODS

Seventy-eight patients with pathologically confirmed parotid gland tumors, who underwent DWI and SWI for pre-surgery evaluation, were enrolled. Apparent diffusion coefficient (ADC) and degree of intratumoral susceptibility signal intensity (ITSS) were measured and compared between benign and malignant groups, and among pleomorphic adenoma (PA), Warthin tumor (WT) and malignant tumor (MT). Independent sample t test, one-way analysis of variance and receiver operating characteristic curve analysis were used for statistical analyses.

RESULTS

Benign parotid gland tumor showed a significantly higher mean ADC value than malignant tumors (0.836 ± 0.350 vs 0.592 ± 0.163, p = 0.001). Setting an average ADC value of 0.679 as the cut-off value, optimal differentiating performance could be obtained (AUC, 0.700; sensitivity, 62.69%; specificity, 81.82%) for differentiating malignant from benign tumors. PA showed significantly higher mean ADC and less ITSS than WT (ADC, p < 0.001; ITSS, p = 0.033) and MT (ADC, p < 0.001; ITSS, p = 0.024), while the difference between WT and MT was not significant (ADC, p = 0.826; ITSS, p = 0.539). After integration with ITSS, the diagnostic performance of ADC was improved for differentiating PA from WT (AUC 0.921 vs 0.873) and from MT (AUC 0.906 vs 0.882).

CONCLUSION

SWI could provide added information to DWI and serve as a supplementary imaging marker for the characterization of parotid gland tumors.

Feasibility of using dynamic contrast-enhanced MRI for differentiating thymic carcinoma from thymic lymphoma based on semi-quantitative and quantitative models

AIM

To evaluate the value of using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived parameters to differentiate thymic carcinoma and thymic lymphoma based on semi-quantitative and quantitative models.

MATERIALS AND METHODS

Twenty-nine pathologically confirmed anterior mediastinum tumours in 29 patients were enrolled in this retrospective study, including 15 thymic carcinoma and 14 lymphoma patients. All the patients underwent pre-treatment mediastinum DCE-MRI. Both semi-quantitative and quantitative parameters were calculated and the volume transfer constant K^trans, the flux rate constant between extravascular extracellular space and plasma k_ep, the extravascular extracellular volume fraction v_e were obtained based on a modified Tofts model. DCE-MRI derived parameters were compared between thymic carcinoma and thymic lymphoma groups.

RESULTS

Thymic carcinoma had significantly lower k_ep (p=0.040) and higher v_e (p=0.018) than thymic lymphoma; however, there were no significant differences on K^trans and semi-quantitative parameters between the two groups. v_e had the highest area under the curve (cut-off value, 0.282; area under the curve, 0.748; sensitivity, 71.4%; specificity, 80%). The combination of k_ep and v_e could increase the diagnostic performance significantly (area under the curve, 0.752; sensitivity, 57.1%; specificity, 93.3%).

CONCLUSION

DCE-MRI derived parameters may have value in the differentiating thymic carcinoma and thymic lymphoma.

Differentiation between orbital malignant and benign tumors using intravoxel incoherent motion diffusion-weighted imaging: Correlation with dynamic contrast-enhanced magnetic resonance imaging

To evaluate the performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for differentiating orbital malignant from benign tumors, and to assess the correlation between IVIM-DWI parameters and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters.Twenty-seven patients (17 benign and 10 malignant) with orbital tumors underwent 3.0T MRI examination for pre-treatment evaluation, including IVIM-DWI and DCE-MRI. IVIM-DWI parameters (tissue diffusivity, D; pseudo-diffusion coefficient, D; and perfusion fraction, f) were quantified using bi-exponential fitting model. DCE-MRI parameters (K, the volume transfer constant between the plasma and the extracellular extravascular space [EES]; Ve, the volume fraction of the EES, and Kep, the rate constant from EES to blood plasma) were quantified using modified Tofts model. Independent-sample t test, receiver operating characteristic curve analyses and Spearman correlation test were used for statistical analyses.Malignant orbital tumors showed lower D (P <.001) and higher D (P = .002) than benign tumors. Setting a D value of 0.966 × 10 mm/s as the cut-off value, a diagnostic performance (AUC, 0.888; sensitivity, 100%; specificity, 82.35%) could be obtained for diagnosing malignant tumors. While setting a D value of 42.371 × 10 mm/s as cut-off value, a diagnostic performance could be achieved (AUC, 0.847; sensitivity, 90.00%; specificity, 70.59%). Poor or moderated correlations were found between IVIM-DWI and DCE-MRI parameters (D and Kep, r = 0.427, P = .027; D and Ve, r = 0.626, P <.001).IVIM-DWI is potentially useful for differentiating orbital malignant from benign tumors. Poor or moderate correlations exist between IVIM-DWI and DCE-MRI parameters. IVIM-DWI may be a useful adjunctive perfusion technique for the differential diagnosis of orbital tumors.

Combining tumor size and diffusion-weighted imaging to diagnose normal-sized metastatic pelvic lymph nodes in cervical cancers

BACKGROUND

Detecting normal-sized metastatic pelvic lymph nodes (LNs) in cervical cancers, although difficult, is of vital importance.

PURPOSE

To investigate the value of diffusion-weighted-imaging (DWI), tumor size, and LN shape in predicting metastases in normal-sized pelvic LNs in cervical cancers.

MATERIAL AND METHODS

Pathology confirmed cervical cancer patients with complete magnetic resonance imaging (MRI) were documented from 2011 to 2016. A total of 121 cervical cancer patients showed small pelvic LNs (<5 mm) and 92 showed normal-sized (5-10 mm) pelvic LNs (39 patients with 55 nodes that were histologically metastatic, 53 patients with 71 nodes that were histologically benign). Preoperative clinical and MRI variables were analyzed and compared between the metastatic and benign groups.

RESULTS

LN apparent diffusion coefficient (ADC) values and short-to-long axis ratios were not significantly different between metastatic and benign normal-sized LNs (0.98 ± 0.15 × 10^-3 vs. 1.00 ± 0.18 × 10^-3 mm²/s, P = 0.45; 0.65 ± 0.16 vs. 0.64 ± 0.16, P = 0.60, respectively). Tumor ADC value of the metastatic LNs was significantly lower than the benign LNs (0.98 ± 0.12 × 10^-3 vs. 1.07 ± 0.21 × 10^-3 mm²/s, P = 0.01). Tumor size (height) was significantly higher in the metastatic LN group (27.59 ± 9.18 mm vs. 21.36 ± 10.40 mm, P < 0.00). Spiculated border rate was higher in the metastatic LN group (9 [16.4%] vs. 3 [4.2%], P = 0.03). Tumor (height) combined with tumor ADC value showed the highest area under the curve of 0.702 ( P < 0.00) in detecting metastatic pelvic nodes, with a sensitivity of 59.1% and specificity of 78.8%.

CONCLUSIONS

Tumor DWI combined with tumor height were superior to LN DWI and shape in predicting the metastatic state of normal-sized pelvic LNs in cervical cancer patients.

Histogram analysis of dynamic contrast-enhanced magnetic resonance imaging for differentiating malignant from benign orbital lymphproliferative disorders

BACKGROUND

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been used for assessing orbital lymphoproliferative disorders (OLPDs). However, only the mean values of quantitative parameters were obtained in previous studies and tumor heterogeneity was ignored.

PURPOSE

To assess the value of DCE-MRI derived histogram parameters in differentiating malignant from benign OLPDs.

MATERIAL AND METHODS

Forty-eight OLPDs patients (25 malignant and 23 benign) who had undergone DCE-MRI for pre-treatment evaluation were retrospectively included. Histogram parameters of K^trans, k_ep, and v_e were calculated and compared between two groups using the independent sample's t-test. Receiver operating characteristic (ROC) curve analyses were used to determine the diagnostic value of each significant parameter. Multivariate stepwise logistic regression analysis was used to identify the independent predictors of malignant OLPDs.

RESULTS

Tenth k_ep, mean k_ep, median k_ep, and 90th k_ep were significantly higher in the malignant OLPD group than in the benign OLPD group. Tenth v_e was significantly lower in the malignant OLPD group than in the benign OLPD group. Ninetieth k_ep was the only independent predictor of malignant OLPDs ( P = 0.019), with an area under ROC curve of 0.828, a sensitivity of 92.00%, and a specificity of 78.26% at a cut-off value of 1.057 min^-1.

CONCLUSION

Histogram analysis of DCE-MRI derived parameters may help to differentiate malignant from benign OLPDs. The 90th k_ep hold the potential as an independent predictor for malignant OLPDs.

Differentiation of orbital lymphoma and idiopathic orbital inflammatory pseudotumor: combined diagnostic value of conventional MRI and histogram analysis of ADC maps

Background

The overlap of morphological feature and mean ADC value restricted clinical application of MRI in the differential diagnosis of orbital lymphoma and idiopathic orbital inflammatory pseudotumor (IOIP). In this paper, we aimed to retrospectively evaluate the combined diagnostic value of conventional magnetic resonance imaging (MRI) and whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in the differentiation of the two lesions.

Methods

In total, 18 patients with orbital lymphoma and 22 patients with IOIP were included, who underwent both conventional MRI and diffusion weighted imaging before treatment. Conventional MRI features and histogram parameters derived from ADC maps, including mean ADC (ADC_mean), median ADC (ADC_median), skewness, kurtosis, 10th, 25th, 75th and 90th percentiles of ADC (ADC₁₀, ADC₂₅, ADC₇₅, ADC₉₀) were evaluated and compared between orbital lymphoma and IOIP. Multivariate logistic regression analysis was used to identify the most valuable variables for discriminating. Differential model was built upon the selected variables and receiver operating characteristic (ROC) analysis was also performed to determine the differential ability of the model.

Results

Multivariate logistic regression showed ADC₁₀ (P = 0.023) and involvement of orbit preseptal space (P = 0.029) were the most promising indexes in the discrimination of orbital lymphoma and IOIP. The logistic model defined by ADC₁₀ and involvement of orbit preseptal space was built, which achieved an AUC of 0.939, with sensitivity of 77.30% and specificity of 94.40%.

Conclusions

Conventional MRI feature of involvement of orbit preseptal space and ADC histogram parameter of ADC₁₀ are valuable in differential diagnosis of orbital lymphoma and IOIP.

MR-based radiomics signature in differentiating ocular adnexal lymphoma from idiopathic orbital inflammation

OBJECTIVES

To assess the value of the MR-based radiomics signature in differentiating ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI).

METHODS

One hundred fifty-seven patients with pathology-proven OAL (84 patients) and IOI (73 patients) were divided into primary and validation cohorts. Eight hundred six radiomics features were extracted from morphological MR images. The least absolute shrinkage and selection operator (LASSO) procedure and linear combination were used to select features and build radiomics signature for discriminating OAL from IOI. Discriminating performance was assessed by the area under the receiver-operating characteristic curve (AUC). The predictive results were compared with the assessment of radiologists by chi-square test.

RESULTS

Five radiomics features were included in the radiomics signature, which differentiated OAL from IOI with an AUC of 0.74 and 0.73 in the primary and validation cohorts respectively. There was a significant difference between the classification results of the radiomics signature and those of a radiology resident (p < 0.05), although there was no significant difference between the results of the radiomics signature and those of a more experienced radiologist (p > 0.05).

CONCLUSIONS

Radiomics features have the potential to differentiate OAL from IOI.

KEY POINTS

• Clinical and imaging findings of OAL and IOI often overlap, which makes diagnosis difficult. • Radiomics features can potentially differentiate OAL from IOI non invasively. • The radiomics signature discriminates OAL from IOI at the same level as an experienced radiologist.

Characterization of diffuse orbital mass using Apparent diffusion coefficient in 3-tesla MRI

Purpose

To evaluate if the apparent diffusion coefficient (ADC) value in diffusion-weighted magnetic resonance imaging (DW-MRI) improves the diagnostic accuracy of diffuse orbital masses.

Materials and methods

ADC DW-MRI was used to evaluate cases of diffuse orbital masses at our institution from 2000 to 2015. Lesions were grouped according to histopathologic diagnosis as, benign, pre-malignant and malignant. Lymphoproliferative lesions were further subgrouped as lymphoma or other lymphoproliferative lesions. The validity of the ADC value for the diffuse orbital mass was compared between groups. The area under curve (AUC) was also calculated.

Results

Thirty-nine cases of diffuse orbital masses were evaluated. The median ADC was 0.58 (25% quartile 0.48; minimum: 0.45; maximum: 1.72 × 10⁽⁻³⁾) for the malignant tumors and 1.19 (25% quartile 0.7; minimum: 0.5; maximum: 1.95 × 10⁽⁻³⁾ mm⁽²⁾ s⁽⁻¹⁾) for benign lesions. This difference in ADC between lesions was statistically significant (Mann Whitney U test P < 0.001). The median ADC was 0.51 (25% quartile 0.48) for lymphomas and 0.9 (25% quartile 0.7) for other lymphoproliferative lesions. This difference in ADC was statistically significant (Mann Whitney U test P = 0.02). An ADC value of 0.8 × 10⁽⁻³⁾ mm⁽²⁾ s⁽⁻¹⁾ was noted as the ideal threshold value for differentiating malignant from benign diffuse orbital masses. The validity of ADC in predicting a malignant or benign diffuse orbital mass had a sensitivity of 87%, specificity of 67% and accuracy of 88%.

Conclusion

ADC is a promising imaging metric to characterize malignant and benign diffuse orbital masses and to distinguish lymphomas from other non−lymphoproliferative lesions.

Repeatability of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0 Tesla in orbital lesions

OBJECTIVES

To evaluate repeatability of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) parameters in the orbit.

METHODS

From December 2015 to March 2016, 22 patients were scanned twice using an IVIM sequence with 15b values (0-2,000 s/mm2) at 3.0T. Two readers independently delineated regions of interest in an orbital mass and in different intra-orbital and extra-orbital structures. Short-term test-retest repeatability and inter-observer agreement were assessed using the intra-class correlation coefficient (ICC), the coefficient of variation (CV) and Bland-Altman limits of agreements (BA-LA).

RESULTS

Test-retest repeatability of IVIM parameters in the orbital mass was satisfactory for ADC and D (mean CV 12% and 14%, ICC 95% and 93%), poor for f and D*(means CV 43% and 110%, ICC 90% and 65%). Inter-observer repeatability agreement was almost perfect in the orbital mass for all the IVIM parameters (ICC = 95%, 93%, 94% and 90% for ADC, D, f and D*, respectively).

CONCLUSIONS

IVIM appeared to be a robust tool to measure D in orbital lesions with good repeatability, but this approach showed a poor repeatability of f and D*.

KEY POINTS

• IVIM technique is feasible in the orbit. • IVIM has a good-acceptable repeatability of D (CV range 12-25 %). • IVIM interobserver repeatability agreement is excellent (ICC range 90-95 %). • f or D* provide higher test-retest and interobserver variabilities.

Readout-segmented echo-planar diffusion-weighted imaging in the assessment of orbital tumors: comparison with conventional single-shot echo-planar imaging in image quality and diagnostic performance

Background Readout-segmented echo-planar imaging (RS-EPI) could improve the imaging quality of diffusion-weighted imaging (DWI) in various organs. However, whether it could improve the imaging quality and diagnostic performance for the patients with orbital tumors is still unknown. Purpose To compare the image quality and diagnostic performance of RS-EPI DWI with that of conventional single-shot EPI (SS-EPI) DWI in patients with orbital tumors. Material and Methods SS-EPI and RS-EPI DW images of 32 patients with pathologically diagnosed orbital tumors were retrospectively analyzed. Qualitative imaging parameters (imaging sharpness, geometric distortion, ghosting artifacts, and overall imaging quality) and quantitative imaging parameters (apparent diffusion coefficient [ADC], signal-to-noise ratio [SNR], contrast, and contrast-to-noise ratio [CNR]) were assessed by two independent radiologists, and compared between SS-EPI and RS-EPI DWI. Receiver operating characteristic curves were used to determine the diagnostic value of ADC in differentiating malignant from benign orbital tumors. Results RS-EPI DW imaging produced less geometric distortion and ghosting artifacts, and better imaging sharpness and overall imaging quality than SS-EPI DWI (for all, P < 0.001). Meanwhile, RS-EPI DWI produced significantly lower SNR ( P < 0.001) and ADC ( P < 0.001), and higher contrast ( P < 0.001) than SS-EPI DWI, while producing no difference in CNR ( P = 0.137). There was no significant difference on the diagnostic performance between SS-EPI and RS-EPI DWI, when using ADC as the differentiating index ( P = 0.529). Conclusion Compared with SS-EPI, RS-EPI DWI provided significantly better imaging quality and comparable diagnostic performance in differentiating malignant from benign orbital tumors.

Combined diffusion-weighted imaging and dynamic contrast-enhanced MRI for differentiating radiologically indeterminate malignant from benign orbital masses

AIM

To evaluate the performance of the combination of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for differentiating radiologically indeterminate malignant from benign orbital masses.

MATERIALS AND METHODS

Sixty-five patients with orbital masses (36 benign and 29 malignant) underwent DW and DCE MRI examinations for pre-treatment evaluation. The apparent diffusion coefficient (ADC) was derived from DW imaging data using the mono-exponential model. The volume transfer constant (K^trans), the flux rate constant between the extravascular extracellular space and the plasma (K_ep), and the extravascular extracellular volume fraction (V_e) were calculated using modified Tofts model. Differences in quantitative metrics were tested using independent-samples t test. Receiver operating characteristic (ROC) curve analyses were used to determine and compare the diagnostic ability of each significant metric.

RESULTS

The malignant group demonstrated significantly lower ADC (0.711±0.260 versus 1.187±0.389, p<0.001) and higher K_ep values (1.265±0.637 versus 0.871±0.610, p=0.008) than the benign group. Optimal diagnostic performance (area under the ROC curve [AUC], 0.941; sensitivity, 0.966; specificity, 0.917) could be achieved using combined ADC and K_ep values as the diagnostic index. The diagnostic performance of the combination of ADC and K_ep was significantly better than K_ep alone (p=0.006). Compared with ADC alone, combined ADC and K_ep values also showed higher AUC (0.941 versus 0.898), although the difference did not reach statistical significance (p=0.220).

CONCLUSION

K_ep and ADC could help to differentiate radiologically indeterminate malignant from benign orbital masses. The combination of DW and DCE MRI might improve the differentiating performance.

Lymphoma and inflammation in the orbit: Diagnostic performance with diffusion-weighted imaging and dynamic contrast-enhanced MRI

PURPOSE

To investigate the diagnostic performance of diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and the combination of both in the differential diagnosis of lymphoma and inflammation in the orbit.

MATERIALS AND METHODS

This retrospective study was approved by the Institutional Review Board and the informed consent requirement was waived. A total of 53 patients underwent preoperative 3T MRI. Parameters of DWI and DCE MRI were evaluated in these 30 patients with orbital lymphoma and 23 patients with orbital inflammation. The diagnostic performance was evaluated using receiver operating characteristic curve analysis.

RESULTS

Apparent diffusion coefficient (ADC) values and parameters derived from DCE MRI of orbital lymphoma and orbital inflammation differed significantly (ADC, T_max , contrast index [CI], enhancement ratio [ER], and washout ratio [WR]: P < 0.001, P = 0.008, P < 0.001, P < 0.001, and P = 0.005 for reviewer 1, respectively; P < 0.001, P = 0.004, P < 0.001, P < 0.001, and P < 0.001 for reviewer 2, respectively). Sensitivity, specificity, and accuracy values of DWI were 76.67%, 100%, and 86.79% for reviewer 1; 70%, 95.65%, and 81.13% for reviewer 2, respectively. The combination of both were 90%, 86.96%, and 88.68% for reviewer 1; 93.33%, 78.26%, and 86.79% for reviewer 2, respectively. The combination of both was significantly superior to DWI for differentiation of orbital lymphoma from orbital inflammation (P = 0.016 for reviewer 1; P = 0.001 for reviewer 2).

CONCLUSION

The combination of DWI and DCE MRI can improve diagnostic performance in differentiating lymphoma from inflammation in the orbit compared with DWI alone.

LEVEL OF EVIDENCE

3 J. MAGN. RESON. IMAGING 2017;45:1438-1445.